Digital Transformation in Resource-Constrained Airlines: An Integrated Framework for Emerging Markets

While digital transformation has become essential for airline competitiveness, resource-constrained carriers in emerging markets face severe barriers, including limited capital, inadequate infrastructure, and human capital shortages. This systematic literature review synthesizes 60 peer-reviewed studies to identify digital transformation strategies, challenges, and opportunities for these airlines. Employing an integrated theoretical framework combining the technology acceptance model (TAM), resource-based view (RBV), and FORMULA 4.0 Digital Transformation Framework, the review demonstrates that successful transformation depends not solely on technology adoption but on the strategic alignment of user acceptance, organizational capabilities, and phased implementation. Four key strategies emerged: lean digital adoption, strategic automation, customer-centric digital touchpoints, and data-driven resource optimization. Five principal challenges were identified: severe financial constraints, infrastructural deficiencies, human capital limitations, cybersecurity risks, and competitive disadvantages. Despite these barriers, opportunities exist through strategic adaptation, supportive policy environments, niche market focus, and incremental digital maturity. The review advances three theoretical propositions for empirical testing and proposes a phased prioritization framework for implementation. Findings indicate that resource-constrained airlines can achieve sustainable digital transformation by prioritizing affordable, high-impact initiatives that leverage existing organizational resources through carefully sequenced implementation. This integrated framework extends existing aviation digital transformation literature by providing context-sensitive guidance particularly suited to emerging-market carriers, offering both theoretical contributions and practical roadmaps for managers navigating digital transformation under severe resource constraints.